Developing Software For Multi-Core CPUs - Do Programs Have To Be Manually Optimised To Use All Cores? Or Does This Occur Automatically?

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The vast majority of CPUs coming out nowadays contain multiple cores which can operate at the same time - in parallel.

I'm just wondering, from the point of executing a program as quickly as possible using all available CPU cores, does a programmer need to take into consideration that the software being developed will be running on a multi-core CPU? For instance, would the software being developed have to be manually configured to assign different tasks to each CPU core? Or does the OS/CPU automatically identify and choose which parts of a program can run - in parallel - on different cores?

Apologies if this may seem like a simple or silly question. I'm completely new to the topic of parallel programming and I've come across some conflicting information early on in my research - some sources state that the programmer must manually configure their software in order to utilise more than one CPU core (the more believable option in my opinion) - and other sources state that the OS/CPU automatically identifies and chooses which tasks can be run in parallel on different CPU cores (the less believable option in my opinion due to the complexity involved in automatically identifying this).

Just in case different Operating Systems, CPUs or Programming Languages perform differently in a parallel computing or multi-core environment - I will be using Windows 7 as my OS, an Intel Dual Core i7 Processor, and OpenCL as the programming language.

Any help is much appreciated.

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windows-7parallel-processingmultiprocessingopenclcpu
The simplest approach is to use threads - threads will typically get scheduled on different cores by the OS. Your code will then run fine with a single core, but will take advantage of multiple cores if they are available. If your program is only single-threaded though, then you won't get any significant benefit from multiple cores. - Paul R
msdn.microsoft.com/en-us/library/hh875062.aspx - Hans Passant

1 Answers

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In practice this occurs semi-automatically. More detailed answer will depend on your application nature, preferred programming model and target architecture.

More explanation:

In order to exploit multicore hardware efficiently (in your case, keeping as much cores busy as possible) you first of all 1) need to "parallelize" algorithm itself - make it "concurrent", 2) use one of multi-threading (most often) or multi-process (rare case) parallel programming APIs, like for example "OpenMP", "Intel TBB", "OpenCL", "Posix Threads" or (for multi-process) "MPI" in order to efficiently and often automatically assign different "pieces" of your concurrent program to different threads (or, rare case, processes).

One of the simplest possible examples of such kind of parallel programming (using OpenMP) is given here.

Now, you've told that you are using OpenCL as a programming model for CPU. In certain cases, when you use vendor-provided OpenCL implementations (like Intel OpenCL) you could semi-automatically assign OpenCL kernel to be executed by various threads using "NDRange" and other OpenCL concepts, like explained here for Intel Xeon Phi co-processor (not exactly CPU-programming, but similar idea) or here (more general, but more advanced article).

However, using OpenCL as a general-purpose multi-threading programming API for CPU - is definitely not the simplest approach; and it is not always optimal in terms of final performance. There are certain application types, where OpenCL makes some little sense for general-purpose CPU multi-threading programming, but again it very much depends on your algorithm nature and target architecture..

There is one very obsolete, but still reasonable post about OpenCL vs. OpenMP/TBB on stackoverflow. This is obsolete in sense that OpenMP 4.0 now also provides solid capabilities to do Threading*+SIMD* programming (which will make you interested in some future if you explore given topic in more details). That's why I would tell that OpenMP seems to be number-one choice nowadays, bug TBB, MPI or OpenCL might also be appropriate in certain cases.